Project Description
Learning new languages is a difficult and time-consuming activity. Our goal is to solve the problem of immersive language learning in Chinese. Our solution is Accent, an app which breaks lessons and reviews into small pieces that can be completed in a matter of minutes with the help of a smartwatch. The user can then take the learning with them so they can learn whenever they have a spare minute. Our app is also context-aware, so it provides vocabulary and lessons that are relevant to the user at that moment. This provides a more immersive experience which will improve recall.
Brainstorming Process
We began our project with several brainstorming sessions in which we tried to gather together as many ideas as we could. This started with very little direction, going for as much breadth as possible. In the end, we had 66 distinct ideas for an app which could make use of a smartwatch. We narrowed all of these ideas down to Quiz Time, an app which would spontaneously give the user quizzes on their watch throughout the day to help them learn, and Safety Reports, an app that would use your location to give you live crime and safety information. As we were trying to decide between these two applications, we leapt from the idea of generic quizzes to an app specifically for learning languages. We felt this idea had the most potential and name it Language Time, which would later become Accent.
The idea was that learning a language has a high barrier to entry due to the large amount of time involved. We could reduce this barrier by using the free moments throughout the day to give small quizzes, thus helping busy individuals such as international business men and women. The watch makes this possible by providing an interface which the user can conveniently access at any time. As we began working with this idea, we saw some additional potential for increasing the immersion of the language-learning process. By using location data, the user could receive words which are relevant to their current context. For example, if you entered a cafe it might suggest words such as coffee to you which are relevant to your immediate surroundings and you can put to use right away. These ultimately became the main two tasks which our app performed: context-aware word suggestions and quizzes integrated throughout the user’s day. In order to be able to focus our efforts we decided to teach Mandarin Chinese, a language which is very important in international business.
Intermediate and Final Design Sketches, Variations, and Ideas
Initially when we decided upon working on a language learning application, our goal was to have a full blown language learning application that encompassed every feature that exists as a part of learning a language. This included learning sentence structuring, grammar, verb conjugation, tenses, pronunciation, phrases, vocabulary, and so much much. In addition to this, there are a countless number of languages out there and so upon realizing this, as a group, we settled to begin with a focus on one specific language. In the end, we made the decision to work on Mandarin from the realization that China is a big market economy and increasingly becoming a bigger player in international trade. Starting off, we sought to replace existing language learning solutions as we saw a void between what users wanted to learn and what lesson plans exactly delivered. Some of our earlier sketches:
Our initial sketches turned into .ai files. Initial prototyping:
However, our plan changed - thus as a result, our design changed. Instead of seeking to replace existing language learning applications, we turned to compliment them. Our design changed to become a part of other language learning tools through quizzing and customizable vocabulary lists where users can have relevance in their learning of a language and retain what is learned through integration of pop quizzes on the smart watch.
In summary, current language learning tools weren’t doing a bad job - we did not want to replace them. Therefore we altered our design space so that our application can be one that helps users further get that learning experience and achieve the language learning goals they desire. For example, if a user’s goal was to be able to order a cappuccino in Mandarin, our application would aid the user to achieving this through contextual discovery from geo-location tracking.
Competitive Analysis
The market for language learning applications is very large, so we had to carefully look at our competitors to see what could set us apart. We focused our evaluation on three of our main competitors within the Chinese language market, as well as the language learning market in general.
The first was Bravolol’s Learn Chinese, which we chose largely because it also only teaches Mandarin Chinese. Bravolol’s Learn Chinese app targets users that just want to learn basic phrases, focusing primarily on tourists. This differs from our target user group of international business people who need to learn the language in much more depth. The basic functionality of the app is that it can play common phrases for the users while displaying the pronunciation. Users are then able to record themselves so that they can self-assess their pronunciation. Our idea will provide feedback rather than requiring purely self-assessment, and will also provide scheduling so the user doesn’t simply go down a list to try to memorize the phrases. The app is very simple and easy to use, however it makes it difficult to learn a large number of phrases since you only have the option of working linearly through lists. This makes reviewing and memorizing difficult if you need more than a few key phrases.
The second is Duolingo, a very popular language learning app which does not yet support Chinese. Duolingo is one of the few language learning applications that is currently available on a smartwatch interface. The application is free and offers a large variety of languages. Their target user group consists of busy individuals looking to learn a language in their limited free time. The smartwatch interface for Duolingo functions similarly to a flash card application. Unlike the smartphone application, the smartwatch version uses self reported assessments. When the application is loaded, the user is presented with a view asking whether they want to practice their selected language. Upon swiping up, a word appears and a timer starts to tick down. The next view queries the user whether they were right or wrong. In comparison to our application, Duolingo does not offer a context aware experience. It also does not utilize an optimal reinforcement schedule. Furthermore, Duolingo does not incorporate written or verbal input in the watch application. To differentiate ourselves, we will be targeting a segment of users with a greater valuation of their time.
The last app we evaluate was Fluenz which is a language learning platform that is targeting a higher end market. The software unlike Duolingo is not free. In fact, the product package costs from $300 up to $700. Their website mentions that they are the preferred language learning software of many fortune 500 executives, students of the Harvard business school and other leading universities. The Fluenz software platform includes a mobile, web, and desktop application, and the experience closely resembles that of a traditional language course. Their main product feature is an “English-speaking sherpa” who guides the user through every lesson. Fluenz does not offer the best casual learning experience. Rather, it appears that they focus more on a user segment that is more dedicated to learning a language. Additionally, it is left to the user to determine their skill level and manage their curriculum. The mobile software also appears to simply be adapted from the desktop version and offers little to no interactivity. In contrast, our application would offer a much more dynamic and interactive experience similar to Duolingo. However, unlike Duolingo, we’re looking to target a higher end market similar to Fluenz and therefore would want to include some of the elements of a traditional language course.
By reviewing these competitors, we found that the main thing that current language learning apps do well is general vocabulary. They provide a more flexible means of learning very general lessons than a standard textbook or class would. Duolingo is probably the strongest competitor in this regard, however it notably lacks Chinese. None of our competitors have any sort of scheduling or context-awareness which is the unique value of our app. These features will allow for our app to be much more immersive than these competitors and thus improve the learning process.
Wireframes
Persona
Our persona is Julie, a 30 year old businesswoman at a global tech firm. She works closely with a team in China, which means she’s constantly travelling back and forth for business meetings. Julie wants to learn Mandarin Chinese in order to connect with her Chinese co-workers. However, she has limited free time and prefers to learn work-related words.
Scenarios
When considering our persona, we determined three tasks that Julie may want to do using our app. The first is selecting relevant vocabulary. Our app allows users to add vocabulary in two ways: the first is to add lists/words themselves. This allows users to take advantage of predefined lists in other language learning software by importing them or add words that they want to learn. The second method is via contextual suggestion. Should the app notice that the user is in an environment with an associated list, the app will notify the user. For instance, if Accent has a predefined set of “restaurant words” and the user walks into a restaurant, the app will present these “restaurant words” to the user as a suggested list. This allows users to learn words that are relevant to their daily lives when they need them. Traditionally, users can either learn from predefined lists or add words themselves. If a user walks into a restaurant or a cafe and realizes that she doesn’t know those words, she may not have the option to learn those words herself. With our app, the user is given words she might find useful before she finds herself in need of them.
The second scenario is when our user wants to practice. Our app schedules practice time for the user by sending quick one-question quizzes to the user’s smart-watch throughout the day. This takes the stress off of busy users and allows them to learn at a reasonable pace, even then they are at their most busy. The user receives a notification on his watch, accepts the quiz, and answers the question: all within a minute. Traditionally, language learners are required to set aside their own time to study, which can result in users forgetting about the language entirely when they get busy.
The third scenario is learning Chinese calligraphy. Brush order is difficult to learn without an app. It’s much easier for users if technology keeps track of the strokes as the user makes them, instead of the user committing that sequence to memory. Our app keeps track of stroke order for the user and gives them a place to practice their calligraphy. Most language learning technology does not allow for users to practice calligraphy or will require the user write with a mouse, which does not have the same results as the user’s finger.
User Studies, Details, and Findings
Our target users are ideally international business people who are either currently Chinese language learners or who want to be in the future as our app is a formal Chinese language-learning app. However for our contextual inquiries and interviews we opened it up to include Japanese language learners (who also may or may not be business people) as well in order to make things simpler in finding interviewees. This was decided based upon the similarity of Japanese to the Chinese language. Japanese is similar to Chinese in two important ways: first, both languages’ writing systems make use of Chinese logographic forms (hanzi in Mandarin, kanji in Japanese) which have their meanings and readings (how the character is spoken) memorized. Given that Chinese-learners would face these challenges as well, Japanese is an appropriate substitute for Mandarin in this context. For our three interviewees, we were able to interview one Chinese language learner (User K)and two Japanese language learners (Users A & C).
User A has a motivated interest in learning Japanese. User A comes from a Chinese background and does know how to speak Chinese fluently as well as accurately. They work at Kikkoman – a Japanese international food & drink company and has worked there for over 10 years. User A’s engagement with learning is moderate and varies in the amount of time spent in learning Japanese. User A has to know Japanese for their work, to converse in conference calls with international partners and co-workers overseas. User A continuously learns Japanese and believes that learning more and more of it is beneficial to their work and job advancement.
From the contextual inquiry with User A, we found that they mainly learn in an auditory fashion. They listen to other speakers such as co-workers and try to pair the Japanese words and phrases with familiar words in Chinese in order to learn. With this method, they are able to ask for immediate feedback from those around them. User A also tends to use Google for translations and research in Japanese. User A further noted that it is difficult to to learn the differences between formal and casual structure, and that conversing with fluent speakers helps reinforce these skills.
User C is learning Japanese for a class. We selected to interview this user because they enjoy learning languages, and so a contextual inquiry could reveal “tried and true” ways of learning languages. They have taken courses in French and Spanish before, and is proficient in Mandarin Chinese. Importantly, they are not learning Japanese for use in business necessarily. Rather, they enjoy learning languages and Japanese was next on their list. User C enjoys learning vocabulary in particular. They mentioned the joy of being able to describe new objects and environments in a language they are learning. User C dislikes learning grammar, citing the difficulty in learning it.
User C studies in a very traditional list and table manner. They have lists of words which they memorize by going down the list and practicing, marking those that aren’t fully memorized yet to repeat later. They particularly liked employing methods using technology or paper to hide the readings for kanji and then going through the list, revealing the readings as they move along. This was a time consuming process which sometimes was difficult since they had to manually cover and uncover the readings. Additionally, User C tends to work a regular time in to schedule in order to practice. They don’t necessarily learn words that they will use in their current environment, but ones for a hypothetical situation in their head.
User K has a very high interest in learning Chinese. User K comes from a Chinese background however did not learn the language as a child growing up as K’s parents also did not learn – K is a 5th generation Asian American. Their engagement with learning is moderate and they wish they could learn more effectively as there is very little time for personal activities in his/her line of study and research work. K does not prioritize his/her sleep going two days in the week without it. K likes learning about global current events and staying up to date with it. K believes that learning Chinese now will prove beneficial when he/she goes to work in a global/international public relations career in the future.
User K employs three main activities to learn Chinese. These are listening to Chinese recordings and following along in a textbook, practicing vocabulary through repeating pronunciation while writing out the Characters, and forcing themselves to use Chinese in writings and speech throughout the day. User K also noted that there isn’t enough of this Chinese audio input throughout their day in order to easily retain what they learned. They are very frustrated that they always have to check their correctness themselves.
From these three users we can begin to see some common trends. Most obvious was the method of self-testing and covering words to learn vocabulary, a method which they seemed to want to keep for the most part as they are fairly attached to their lists. However, there was also a theme that they wanted to have more learning take place in their daily lives and to pertain to those environments so they could routinely practice. Finally, they all also desired more feedback so they didn’t have to rely on their intuition.
Final Design
Discovering Context-Specific Words
Half of Accent's value is the ability to adapt the words that the user is learning in order to match their environment. Users regularly "discover" words that relate to their surroundings. For example, Accent discovers a list of words that one uses to order coffee while the user is in a cafe.
Integrating Lists
After discovering new context-aware words, users can integrate them into the curriculum they are already learning. This task serves Julie's two major needs: the need for a stable and regular language curriculum, and the need to learn words that are appropriate with her physical context.
Practicing on the Go
Finally, Accent allows users to practice both their discovered words and their core curriculum words on the watch.
Technical challenges
The main challenges that we faced was approximating our Framer interface on a physical Toq watch. We built out our vision for the app using Illustrator and Framer, which gave us results which we were very happy with and accurately portrayed the interaction flow which we found would be most beneficial from our user studies. However, this concept relied on many features that the Toq does not support, including drawing input for testing calligraphy and voice input for testing pronunciation. Because of this, we had to make Wizard of Oz style modifications to how the actual app functioned so that the Toq could simulate the interactive experience of our Framer designs. Furthermore, we wanted the Toq app to fit stylistically with our entire design. This meant using images on the Toq watch as the interface, which can be difficult to size appropriately while still portraying the same feel.
Ultimately, while our app was not fully functional, we felt that it managed to show users the experience they could expect from the full-fledged Accent app. This would be perfect for performing further user testing for an app on hardware that could support all of this functionality.
Summary of Project
Language barriers pose a challenge for even the most seasoned business person. Accent remedies this challenge by making language-learning relevant and unobtrusive for even the busiest schedules, while at the same time drawing on the effectiveness of already-designed language curriculum. As difficult as language-learning can be, it is still deeply human feature, and emerging smartwatch technology affords learning new vocabulary as if it were a natural reflex. Accent serves to build off the success of more traditional language learning and to keep learning as fluid and second-nature as possible for businesspeople.
Presentation Videos
Notes
Toq code has been shared with cs160 on bitbucket by smcqueenberkeley.
Framer code has been shared with cs160 on bitbucket by madeehamfg
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